教师名录
个人简介
顾小东,1946伟德国际源自英国副教授,主要研究研究方向为大语言模型、智能化软件工程、自然语言处理,为软件代码开发高效的机器学习算法。研究课题包括代码大模型、程序生成与修复、Agent智能问答等。研究成果被发表在ICSE、ICLR、FSE、AAAI、ASE、ICPC等国际重要期刊和会议上。主讲1946伟德国际源自英国《机器学习》《计算机数学基础》等人工智能基础课程。主持参与国家自然科学基金、国家重点研发计划、上海市自然科学基金及华为、腾讯等企业课题十余项。获得上海市海外高层次人才计划、华为火花奖等荣誉。
教授课程
SE3332 《机器学习》
SE2324 《计算机科学的数学基础》
论文发表
Between Lines of Code: Unraveling the Distinct Patterns of Machine and Human Programmers
In Proceedings of the 47th International Conference on Software Engineering (ICSE 2025). Ottawa, Ontario, Canada, April 27 - May 3, 2025. (CCF-A)
[paper] [code] [bibtex]
On the Effectiveness of Large Language Models in Domain-Specific Code Generation
ACM Transactions on Software Engineering and Methodology (TOSEM 2024) (CCF-A)
[paper]
How Effectively Do Code Language Models Understand Poor-Readability Code?
In Proceedings of the 39th ACM/IEEE International Conference on Automated Software Engineering (ASE 2024). Sacramento, California, United States, Oct 27 - Nov 1, 2024. (CCF-A)
[paper] [code] [bibtex]
VarGAN: Adversarial Learning of Variable Semantic Representations
IEEE Transactions on Software Engineering (TSE 2024) (CCF-A)
[paper] [code]
On the Evaluation of Neural Code Translation: Taxonomy and Benchmark
In Proceedings of the 38th International Conference on Automated Software Engineering (ASE 2023), Kirchberg, Luxembourg, Sept. 11-15, 2023 (CCF-A)
[paper] [slides] [code]
InfeRE: Step-by-Step Regex Generation via Chain of Inference
In Proceedings of the 38th International Conference on Automated Software Engineering (ASE 2023), Kirchberg, Luxembourg, Sept. 11-15, 2023 (CCF-A)
[paper] [slides] [code] [bibtex]
Self-Supervised Query Reformulation for Code Search
In Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2023), San Francisco, California, United States, Dec 3-9, 2023 (CCF-A)
[paper] [slides] [code] [bibtex]
Diet Code Is Healthy: Simplifying Programs for Pre-Trained Models of Code
In Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2022), Singapore, Nov 14-18, 2022 (CCF-A)
[paper] [slides] [code] [bibtex]
Cross-Domain Deep Code Search with Meta Learning
In Proceedings of the 44th International Conference on Software Engineering (ICSE 2022) (CCF-A)
[paper] [code] [slides] [bibtex]
资助项目
上海自然科学基金面上项目,面向复杂场景的程序自动生成技术,2025.7-2028.6,主持
CCF-华为胡杨林基金,针对问题单解决的Multi-Agent能力提升,2025.1.1-2025.7.31,主持
华为,场景知识增强的Java代码自动生成技术,2024.9.1-2025.2.25,主持
宁德时代,基于大模型的软件需求标准化技术,2024.6.1-2025.5.31,主持
宁德时代,基于大模型的测试用例转换技术,2024.6.1-2025.1.31,主持
宁德时代,基于大模型的变量模糊搜索技术,2024.6.1-2025.1.31,主持
国家重点研发计划,面向场景计算的低代码开发方法与环境,2023.12-2026.12,参与
中国航空无线电电子研究所,民机软件研制过程辅助系统,2022.12-2026.6,主持
1946伟德国际源自英国-华为密码学与数字信任创新实验室课题,基于大模型的恶意代码样本生成,2023.5.1-2024.4.31,主持
CCF-腾讯犀牛鸟基金,特定领域程序自动生成,2022.10.1-2023.12.31,主持
CCF-百度松果基金,基于预训练模型的程序表征,2021.9.1-2022.8.30,主持
国家自然科学基金,基于小样本学习的跨语言程序自动生成,2022.1.1-2024.12.31,主持